Bo Gong1, James P Nugent2, William Guest3, William Parker4, Paul J Chang5, Faisal Khosa6, Savvas Nicolaou7. 1. MD Undergraduate Program, University of British Columbia, Vancouver, British Columbia, Canada; Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: bogong.ustc@gmail.com. 2. MD Undergraduate Program, University of British Columbia, Vancouver, British Columbia, Canada; Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: james.nugent@alumni.ubc.ca. 3. Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: will.c.guest@gmail.com. 4. Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: will.parker@icloud.com. 5. Department of Radiology, University of Chicago Medical Center, Chicago, Illinois. Electronic address: pchang@radiology.bsd.uchicago.edu. 6. Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: fkhosa@hotmail.com. 7. Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: savvas.nicolaou@vch.ca.
Abstract
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) has the potential to transform the clinical practice of radiology. This study investigated Canadian medical students' perceptions of the impact of AI on radiology, and their influence on the students' preference for radiology specialty. MATERIALS AND METHODS: In March 2018, an anonymous online survey was distributed to students at all 17 Canadian medical schools. RESULTS: Among 322 respondents, 70 students considered radiology as the top specialty choice, and 133 as among the top three choices. Only a minority (29.3%) of respondents agreed AI would replace radiologists in foreseeable future, but a majority (67.7%) agreed AI would reduce the demand for radiologists. Even among first-choice respondents, 48.6% agreed AI caused anxiety when considering the radiology specialty. Furthermore, one-sixth of respondents who would otherwise rank radiology as the first choice would not consider radiology because of the anxiety about AI. Prior significant exposure to radiology and high confidence in understanding of AI were shown to decrease the anxiety level. Interested students valued the opinions of local radiologists, radiology conferences, and journals. Students were most interested in "expert opinions on AI" and "discussing AI in preclinical radiology lectures" to understand the impact of AI. CONCLUSION: Anxiety related to "displacement" (not "replacement") of radiologists by AI discouraged many medical students from considering the radiology specialty. The radiology community should educate medical students about the potential impact of AI, to ensure radiology is perceived as a viable long-term career choice.
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) has the potential to transform the clinical practice of radiology. This study investigated Canadian medical students' perceptions of the impact of AI on radiology, and their influence on the students' preference for radiology specialty. MATERIALS AND METHODS: In March 2018, an anonymous online survey was distributed to students at all 17 Canadian medical schools. RESULTS: Among 322 respondents, 70 students considered radiology as the top specialty choice, and 133 as among the top three choices. Only a minority (29.3%) of respondents agreed AI would replace radiologists in foreseeable future, but a majority (67.7%) agreed AI would reduce the demand for radiologists. Even among first-choice respondents, 48.6% agreed AI caused anxiety when considering the radiology specialty. Furthermore, one-sixth of respondents who would otherwise rank radiology as the first choice would not consider radiology because of the anxiety about AI. Prior significant exposure to radiology and high confidence in understanding of AI were shown to decrease the anxiety level. Interested students valued the opinions of local radiologists, radiology conferences, and journals. Students were most interested in "expert opinions on AI" and "discussing AI in preclinical radiology lectures" to understand the impact of AI. CONCLUSION:Anxiety related to "displacement" (not "replacement") of radiologists by AI discouraged many medical students from considering the radiology specialty. The radiology community should educate medical students about the potential impact of AI, to ensure radiology is perceived as a viable long-term career choice.
Authors: Mawya A Khafaji; Mohammed A Safhi; Roia H Albadawi; Salma O Al-Amoudi; Salah S Shehata; Fadi Toonsi Journal: Saudi Med J Date: 2022-01 Impact factor: 1.422
Authors: Abdulmajeed Bin Dahmash; Mohammed Alabdulkareem; Aljabriyah Alfutais; Ahmed M Kamel; Feras Alkholaiwi; Shaker Alshehri; Yousof Al Zahrani; Mohammed Almoaiqel Journal: BJR Open Date: 2020-12-11